Forensic Breakthrough for Crime Scene Analysis via Mobile Data and NLP Applications Article Swipe

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Krishna Mohan Buddaraju , Khateeb Syed Muskan , Baldev Raj , Jenne Sumithra , Gogula Sai Ganesh , Sachin Kumar ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.33425/3066-1226.1102

With the rise of digital communication, chat logs have become a crucial source of evidence in forensic investigations. The crime scene analysis by integrating Natural Language Processing (NLP) techniques to analyze chat data for identifying key information, suspect behavior, and potential criminal intent. Using advanced NLP methods such as sentiment analysis, named entity recognition, and text classification, it can detect hidden connections, and contextual meanings within conversations. This automated analysis enhances the efficiency and accuracy of forensic investigations, reducing manual effort and enabling law enforcement to make data-driven decisions. By leveraging chat-based forensic analysis, this contributes to modern crime-solving techniques, offering a powerful tool for digital evidence examination. Advancements in Natural Language Processing (NLP) and digital forensics have revolutionized crime scene investigations, particularly in analyzing digital communication for crucial evidence. forensic breakthrough that leverages chat logs and NLP applications to extract, analyze, and interpret conversations relevant to criminal cases. By providing law enforcement agencies with an intelligent and scalable tool for chat-based forensic analysis, this significantly improves digital evidence handling, accelerates crime resolution, and supports judicial proceedings with data-driven insights. It ultimately contributes to modern forensic science by bridging the gap between technology and criminal investigations, making digital communication a key asset in solving crimes efficiently.

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Computer Science

Artificial Intelligence

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Computer science Artificial intelligence Natural language processing

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Type: article
Language: en
Landing Page: https://doi.org/10.33425/3066-1226.1102
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OA Status: hybrid
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DOI: https://doi.org/10.33425/3066-1226.1102

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Title: Forensic Breakthrough for Crime Scene Analysis via Mobile Data and NLP Applications

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Type: article

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Language: en

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Publication year: 2025

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Publication date: 2025-04-22

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Authors: Krishna Mohan Buddaraju, Khateeb Syed Muskan, Baldev Raj, Jenne Sumithra, Gogula Sai Ganesh, Sachin Kumar

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Landing page: https://doi.org/10.33425/3066-1226.1102

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Concepts: Computer science, Artificial intelligence, Natural language processing

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